This application relates generally to signal detection, and more particularly to calculating soft information for a signal obtained from a multi-level modulation system.
With the continuing demand for higher-speed digital communications systems and higher-density digital storage systems, various techniques have been applied to increase the capacity of these systems. However, even with high-capacity communications and storage media, their respective bandwidths and densities are still limited. Therefore, multi-level signaling can be applied to fully utilize the available bandwidth or density of these systems. For example, rather than binary signaling, e.g., 2-PAM, some communications system can increase the amount of information transmitted by using four signal levels, e.g., 4-PAM.
However, determining the information contained within a received signal of a multi-level system may be a complex problem. In particular, at each time interval, a received signal may correspond to a plurality of different digital information sequences, or “symbols.” Typically, to determine the digital information within a signal at given time interval, soft information for each bit of the digital information is computed based on each possible symbol. The soft information typically corresponds to the likelihood that a particular bit is “0” or “1.” Thus, because there can be many possible symbols in multi-level systems, computing soft information at each time interval can require a large amount of high complexity computational circuitry. Furthermore, because these likelihoods may need to be computed frequently, the computational circuitry may also have high power consumption. Accordingly, it would be desirable to provide low complexity and low power techniques for calculating soft information in systems with multi-level modulation.